Create analytics_dashboard.py

analytics_dashboard.py

@@ -0,0 +1,58 @@
+import gradio as gr
+import pandas as pd
+import matplotlib.pyplot as plt
+import json
+from io import BytesIO
+from datetime import datetime
+
+def load_usage_data():
+    """load usage_log.json file to be DataFrame"""
+    try:
+        with open("usage_log.json", "r") as f:
+            data = json.load(f)
+        if not data.get("runs"):
+            return None
+
+        df = pd.DataFrame(data["runs"])
+        df["timestamp"] = pd.to_datetime(df["timestamp"], errors='coerce')
+        df.dropna(subset=["timestamp"], inplace=True)
+        df["date"] = df["timestamp"].dt.date
+        return df
+    except Exception as e:
+        print(f"Error loading usage data: {e}")
+        return None
+
+def plot_daily_usage(df):
+    try:
+        counts = df.groupby("date").size()
+        fig, ax = plt.subplots(figsize=(8, 4))
+        counts.plot(kind="bar", ax=ax, color="#4A90E2")
+        ax.set_title("Daily Usage of PawMatch AI")
+        ax.set_xlabel("Date")
+        ax.set_ylabel("Runs")
+        ax.grid(axis='y', linestyle='--', alpha=0.7)
+        plt.xticks(rotation=45)
+        plt.tight_layout()
+
+        buf = BytesIO()
+        plt.savefig(buf, format="png")
+        plt.close(fig)
+        buf.seek(0)
+        return buf
+    except Exception as e:
+        return f"Error generating plot: {e}"
+
+def create_analytics_tab():
+    def generate_plot():
+        df = load_usage_data()
+        if df is None or df.empty:
+            return "No usage data available."
+        return plot_daily_usage(df)
+
+    with gr.Tab("\ud83d\udcca Usage Analytics"):
+        gr.Markdown("### Daily Usage Trend of PawMatch AI")
+        with gr.Row():
+            img = gr.Image(type="pil", label="Daily Usage", show_label=True)
+        plot_btn = gr.Button("\ud83d\udd04 Refresh")
+
+        plot_btn.click(fn=generate_plot, outputs=[img])